In order to solve multi-constraint 0-1 knapsack problem, a new profit-density is designed, on basis of which, a Hybrid Genetic Algorithm(HGA) based on greedy algorithm is proposed, which uses the binary code to amend the feasible solution, and applies roulette wheel selection method to rectify knapsack resources with insufficient use, and repairs the infeasible solution.The algorithm is compared with other traditional ones.Experimental results show this HGA can promote the speed and accuracy of solving relevant problems efficiently, and is superior.

ZHENG Liping1,HAO Zhongxiao1,2(1.Department of Computer Science and Engineering,Harbin Institute of Technology,Harbin 150001;2.Department of Computer Science and Technology,Harbin University of Science and Technology,Harbin 150080);Genetic Algorithm Based on Hybrid Crossovers for TSP[J];Computer Engineering;2005-20

LI Yong1,CHEN Wenying2,LIU Jia1(1.School of Public Policy and Management,Tsinghua University,Beijing 100084,China;2.Institute of Nuclear and New Energy Technology,Tsinghua University,Beijing 100084,China);Source-sink matching model for CO_2 capture and storage[J];Journal of Tsinghua University(Science and Technology);2009-06

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LI Yong1,CHEN Wenying2,LIU Jia1(1.School of Public Policy and Management,Tsinghua University,Beijing 100084,China;2.Institute of Nuclear and New Energy Technology,Tsinghua University,Beijing 100084,China);Source-sink matching model for carbon capture and storage[J];Journal of Tsinghua University(Science and Technology);2009-06